Method and circuit for indicating quality and accuracy of physiological measurements

ABSTRACT

Sensors and monitors for a physiological monitoring system having capability to indicate an accuracy of an estimated physiological condition. The sensor senses at least one physiological characteristic of a patient and is connectable to a monitor that estimates the physiological condition from signals detected by the sensor. The sensor includes a detector for detecting the signals from the patient which are indicative of the physiological characteristic. The sensor is associated with a memory configured to store data that defines at least one sensor signal specification boundary for the detected signals. The boundary is indicative of a quality of the signals and an accuracy of the physiological characteristic estimated from the signals by the monitor. The sensor further includes means for providing access to the memory to allow transmission of the data that defines the at least one sensor boundary to the monitor.

This application claims the benefit of U.S. Provisional Application Ser.No. 60/129,170, filed Apr. 14, 1999, which is incorporated herein byreference.

BACKGROUND OF THE INVENTION

The present invention relates to physiological monitoring instrumentsand, in particular, monitors and sensors that include mechanisms forindicating a quality of detected signals and accuracy or confidencelevel of physiological measurements estimated from the signals.

Typically, for physiological monitoring instruments that include amonitor and a patient sensor, the monitor is unable to accuratelydetermine a quality of a signal obtained from the sensor. The inventionwill be explained by reference to a preferred embodiment concerningpulse oximeter monitors and pulse oximetry sensors, but it should berealized the invention is applicable to any generalized patient monitorand associated patient sensor. The invention provides a way of moreaccurately determining a quality of a signal detected by a sensor; a wayof determining a relative accuracy of a physiological characteristicderived or calculated from the signal; and a way of delineating atransition boundary between a normal signal for the sensor being used inits normal application, and a signal considered to be abnormal for thesensor being used, to allow a monitor to determine if the sensor isbeing misapplied.

Pulse oximetry is typically used to measure various blood flowcharacteristics including, but not limited to, the blood oxygensaturation of hemoglobin in arterial blood and the heartbeat of apatient. Measurement of these characteristics has been accomplished bythe use of a non-invasive sensor that passes light through a portion ofa patient's blood perfused tissue and photo-electrically senses theabsorption and scattering of light in such tissue. The amount of lightabsorbed and scattered is then used to estimate the amount of bloodconstituent in the tissue using various algorithms known in the art. The“pulse” in pulse oximetry comes from the time varying amount of arterialblood in the tissue during a cardiac cycle. The signal processed fromthe sensed optical signal is a familiar plethysmographic waveform due tothe cycling light attenuation.

The light passed through the tissue is typically selected to be of twoor more wavelengths that are absorbed by the blood in an amount relatedto the amount of blood constituent present in the blood. The amount oftransmitted light that passes through the tissue varies in accordancewith the changing amount of blood constituent in the tissue and therelated light absorption.

To estimate arterial blood oxygen saturation of a patient, conventionaltwo-wavelength pulse oximeters emit light from two light emitting diodes(LEDs) into a pulsatile tissue bed and collect the transmitted lightwith a photodiode (or photo-detector) positioned on an opposite surface(i.e., for transmission pulse oximetry) or an adjacent surface (i.e.,for reflectance pulse oximetry). The LEDs and photo-detector aretypically housed in a reusable or disposable oximeter sensor thatcouples to a pulse oximeter electronics and display unit. One of the twoLEDs' primary wavelength is selected at a point in the electromagneticspectrum where the absorption of oxyhemoglobin (HbO₂) differs from theabsorption of reduced hemoglobin (Hb). The second of the two LEDs'wavelength is selected at a different point in the spectrum where theabsorption of Hb and HbO₂ differs from those at the first wavelength.Commercial pulse oximeters typically utilize one wavelength in the nearred part of the visible spectrum near 660 nanometers (nm) and one in thenear infrared (IR) part of the spectrum in the range of 880-940 nm.

Oxygen saturation can be estimated using various techniques. In onecommon technique, first and second photo-current signals generated bythe photo-detector from red and infrared light are conditioned andprocessed to determine AC and DC signal components and a modulationratio of the red to infrared signals. This modulation ratio has beenobserved to correlate well to arterial oxygen saturation. Pulseoximeters and sensors are empirically calibrated by measuring themodulation ratio over a range of in vivo measured arterial oxygensaturations (SaO₂) on a set of patients, healthy volunteers, or animals.The observed correlation is used in an inverse manner to estimate bloodoxygen saturation (SpO₂) based on the measured value of modulationratios. The estimation of oxygen saturation using modulation ratio isdescribed in U.S. Pat. No. 5,853,364, entitled “METHOD AND APPARATUS FORESTIMATING PHYSIOLOGICAL PARAMETERS USING MODEL-BASED ADAPTIVEFILTERING”, issued Dec. 29, 1998, and U.S. Pat. No. 4,911,167, entitled“METHOD AND APPARATUS FOR DETECTING OPTICAL PULSES”, issued Mar. 27,1990. The relationship between oxygen saturation and modulation ratio isfurther described in U.S. Pat. No. 5,645,059, entitled “MEDICAL SENSORWITH MODULATED ENCODING SCHEME,” issued Jul. 8, 1997. All three patentsare assigned to the assignee of the present invention and incorporatedherein by reference.

The accuracy of the estimates of the blood flow characteristics dependson a number of factors. For example, the light absorptioncharacteristics typically vary from patient to patient depending ontheir physiology. Moreover, the absorption characteristics varydepending on the location (e.g., the foot, finger, ear, and so on) wherethe sensor is applied. Further, the light absorption characteristicsvary depending on the design or model of the sensor. Also, the lightabsorption characteristics of any single sensor design vary from sensorto sensor (e.g., due to different characteristics of the light sourcesor photo-detector, or both). The clinician applying the sensor correctlyor incorrectly may also have a large impact in the results, for example,by loosely or firmly applying the sensor or by applying the sensor to abody part which is inappropriate for the particular sensor design beingused.

Some oximeters “qualify” measurements before displaying them on themonitor. One conventional technique processes (i.e., filters) themeasured plethysmographic waveform and performs tests to detect andreject measurements perceived corrupted and inaccurate. Since oximetersare typically designed to be used with a wide variety of sensors havingwidely differing performance characteristics, the monitor signal“qualification” algorithms are necessarily crude, and often result inonly superficial indications of signal quality, signal reliability, andultimately a confidence level in a patient physiological characteristicestimated or calculated from the signal. In many instances, the monitorsimply discards data associated with low quality signals, but otherwisegives no indication to a healthcare giver as to whether anyphysiological characteristic displayed on a monitor is highly reliableor not. Hence, the signal quality measurements obtained from such crudealgorithms are relatively poor and convey little useful information to acaregiver.

SUMMARY OF THE INVENTION

Accordingly, it is an object of the present invention to provide apatient monitor and sensor which includes means for accurately detectinga quality of a signal detected by the sensor.

Another object of the invention is to provide a monitor and sensor whichincludes means for accurately determining a quality of a physicalcharacteristic estimated from a signal obtained by a sensor.

A further object of the invention is to provide a monitor and sensorwhich includes means for detecting a transition between a signal regimeconsidered normal for the sensor in its usual application, and a signalregime considered to be abnormal.

These and others objects of the invention are achieved by the use of aset of one or more signal specification boundaries. Each boundarydefines a region of a signal quality diagram and corresponds to adifferent level of quality in the detected signals and accuracy orconfidence level of physiological characteristic estimated from thedetected signals. Boundaries can also be defined for and associated withdifferent sensor types and monitor types. The boundaries are typicallystored in a memory and accessed when required.

An embodiment of the invention provides a sensor for sensing at leastone physiological characteristic of a patient. The sensor is connectableto a monitor that estimates a physiological condition from signalsdetected by the sensor. The sensor includes a detector for detecting thesignals from the patient which are indicative of the physiologicalcharacteristic. The sensor is associated with a memory configured tostore data that defines at least one sensor signal specificationboundary for the detected signals. The boundary is indicative of aquality of the signals and an accuracy of the physiologicalcharacteristic estimated from the signals by the monitor. The sensorfurther includes means for providing access to the memory to allowtransmission of the data that defines the at least one sensor boundaryto the monitor.

In an embodiment, the boundary is indicative of a transition between asignal regime considered normal for the sensor in its usual application,and a signal regime considered to be abnormal. The normal regime can beone in which the sensor is likely to be properly applied to the patientand the abnormal regime can be one in which the sensor may havepartially or entirely come off the patient.

Another embodiment of the invention provides a monitor for providing anindication of an accuracy of an estimated physiological condition of apatient. The monitor is connectable to a sensor that detects signalsindicative of at least one physiological characteristic of the patient.The monitor includes at least one receiving circuit and at least oneprocessing circuit. The receiving circuit is configured to receive thesignals indicative of the at least one physiological characteristic anddata defining at least one sensor signal specification boundary for thedetected signals. The processing circuit is configured to estimate thephysiological condition of the patient based on the received signals,compare the received signals against the at least one sensor boundary,and generate the indication of the accuracy of the estimatedphysiological condition. The monitor further includes means forproviding the indication of the accuracy of the estimated physiologicalcondition to a user of the monitor.

Yet another embodiment of the invention provides a pulse oximetry systemthat includes the sensor described above and a pulse oximetry monitor.The monitor has means to determine whether the signals are within anormal regime or an abnormal regime. The system further includes meansfor informing a user of the system as to whether the signal is normal orabnormal.

The foregoing, together with other aspects of this invention, willbecome more apparent when referring to the following specification,claims, and accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a simplified block diagram of an embodiment of a pulseoximeter system;

FIG. 2A shows a diagram of a specific embodiment of a sensor;

FIGS. 2B and 2C show diagrams of specific embodiments in which a memoryis located within the sensor plug and within the sensor cable,respectively;

FIG. 2D shows a diagram of a specific embodiment of a monitor;

FIG. 3 shows a diagram of a simplified optical waveform detected by thesensor;

FIG. 4 shows a signal quality diagram that includes data of the measuredDC and AC components;

FIG. 5 shows a signal quality diagram having defined regionscorresponding to different confidence levels in the saturation estimate;

FIG. 6 shows a signal quality diagram having defined display andnon-display regions (similar to those of FIG. 5) and transition zones;

FIG. 7 shows a flow diagram of an embodiment of the measurement postingprocess of the invention;

FIG. 8 shows a signal quality diagram with data collected from a patientpopulation; and

FIG. 9 shows a signal quality diagram that includes ambiguity contoursplotted over a portion of the display region.

DESCRIPTION OF THE SPECIFIC EMBODIMENTS

The invention is applicable to measurement (or estimation) of oxygensaturation of hemoglobin in arterial blood and patient heart rate. Theinvention will be described in detail with respect to an embodiment forpulse oximetry, but it needs to be realized that the invention hasapplicability to alternate patient monitoring characteristics, such asECG, blood pressure, temperature, etc., and is not to be limited to onlyfor use with oximetry or pulse oximetry.

FIG. 1 shows a simplified block diagram of an embodiment of a pulseoximeter system 100. System 100 includes a pulse oximeter (or monitor)110 that couples via an electrical cable 128 to a sensor 130 that isapplied to a patient 132. Sensor 130 includes a sensor cable 129 and aconnector plug 120. The sensor further has first and second lightsources (e.g., LEDs) and a photo-detector along with suitable componentsto couple these electro-optical components to the electrical cable 128.

As noted above, oxygen saturation can be estimated using varioustechniques. In one common technique, the optical signals are received bythe photo-detector, and conditioned and processed by the oximeter togenerate AC and DC components. These components are then used to computea modulation ratio of the red to infrared signals. The computedmodulation ratio is then indexed against a table to retrieve asaturation estimate corresponding to that modulation ratio.

FIG. 2A shows a diagram of a specific embodiment of sensor 130. Sensor130 includes two or more LEDs 230 and a photodetector 240. Sensor 130may optionally include a memory 236 a and an interface 238. LEDs 230receive drive signals that (i.e., alternately) activate the LEDs. Whenactivated, the light from LEDs 230 passes into a patient's tissues 234.After being transmitted through or reflected from the tissues, the lightis received by photo-detector 240. Photo-detector 240 converts thereceived light into a photocurrent signal, which is then provided to thesubsequent signal-processing unit.

The sensor memory stores data representative of at least one sensorsignal specification boundary and provides the sensor boundary whenrequested. Interface circuit 238 provides signal conditioning, and canalso provide other functions. Through interface circuit 238, data istransferred to and from the sensor memory. Memory 236 a and interfacecircuit 238 can be integrated within one integrated circuit for reducedsize and cost.

The memory associated with the sensor can be physically located in avariety of places. First, it can be located on the body of the sensor,in a vicinity of the photodetector, LEDs, or other sensor components.Or, the memory can be in the sensor cable 129 or the connector plug 120,or in an adapter module that connects to a front of an oximeter, to anoximeter cable, or to a sensor plug or cable.

FIG. 2B shows a diagram of a specific embodiment in which a memory 236 bis located within the connector plug 120. Memory 236 b couples to andinterfaces with external circuitry through some or all signal linesprovided to the sensor plug.

FIG. 2C shows a diagram of a specific embodiment in which a memory 236 cis located within the sensor cable 129. Again, memory 236 c couples toand interfaces with external circuitry through a set of signal lines.

The memory 236 can be implemented as a random access memory (RAM), aFLASH memory, a programmable read only memory (PROM), an erasable PROM(EPROM), an electrically erasable PROM (EEPROM), a write once memory, orother memory technologies capable of write and read operations. In aspecific embodiment, to preserve the data stored in the memory andprevent accidental erasure, the sensor memory can be written only once.This memory characteristic also prevents erasure of the data duringsensor operation. A specific example of a memory device that can bewritten only once is a 2-wire EPROM device available from DallasSemiconductor Corp.

FIG. 2D shows a diagram of a specific embodiment of monitor 110. Areceiving circuit 250 couples to the sensor and the memory associatedwith the sensor for receiving signals detected by the sensor and datafrom the sensor memory. The receiving circuit 250 couples to aprocessing circuit 252 that processes the received signals to generatean estimate of a physiological characteristic. The processing circuit252 can further generate an indication of the quality of the receivedsignal and an indication of the accuracy of the estimated physiologicalcharacteristic. The estimated physiological characteristic andassociated indications are provided to a display unit 254 for display toa user of the monitor.

FIG. 3 shows a diagram of a simplified optical waveform 300 detected bya sensor (e.g., sensor 130). Optical waveform 300 in FIG. 3 canrepresent the detected optical signal for either the red or infraredLED. As shown in FIG. 3, optical waveform 300 includes a periodicpattern that generally corresponds to a patient's heartbeat. Forarrhythmia patient, the waveform may be aperiodic. Waveform 300 includesa series of peaks having a maximum value (Max) and a series of valleyshaving a minimum value (Min). The following quantities are defined:

$\begin{matrix}{{{AC} = {{Max} - {Min}}};} & {{Eq}.\mspace{14mu} (1)} \\{{{DC} = \frac{\left( {{Max} - {Min}} \right)}{2}};} & {{Eq}.\mspace{14mu} (2)} \\{{{{Modulation}\mspace{14mu} {{percentage}\left( {{Mod}\mspace{14mu} \%} \right)}} = {100 \cdot \left( \frac{AC}{DC} \right)}};{and}} & {{Eq}.\mspace{14mu} (3)} \\{{{nAv}\left( {{nanoAmperes}\mspace{14mu} {virtual}} \right)} = {\frac{DC}{{Instrument}\mspace{14mu} {gain}} \cdot \frac{50\mspace{14mu} {mA}}{{actual}\mspace{14mu} {LED}\mspace{14mu} {drive}\mspace{14mu} {current}\mspace{14mu} {in}\mspace{14mu} {mA}}}} & {{Eq}.\mspace{14mu} (4)}\end{matrix}$

where Instrument gain is a gain value that is specific to thecombination of the pulse oximeter and a particular sensor that is usedduring the detection of the pulses in waveform 300. Nanoamperes virtual“normalizes” the signal to a 50 mA LED drive. Many oximeters containservo systems which adjust LED drive intensity to be optimal for aparticular set of monitoring conditions. By normalizing signal levels toa standard assumed LED drive level, it is possible to derive a measureof signal strength which is dependent primarily on the sensor andpatient, and not on particular drive level which the instrument hasselected.

The modulation ratio of the red to infrared signals, sometimes referredto as the “ratio of ratios” (Ratrat), can be approximated as:

$\begin{matrix}{{{Ratrat} \cong \frac{\left( \frac{AC\_ Red}{DC\_ Red} \right)}{\left( \frac{AC\_ IR}{DC\_ IR} \right)}};} & {{Eq}.\mspace{14mu} (5)}\end{matrix}$

where AC_Red and DC_Red are the respective AC and DC components of thered LED, and AC_IR and DC_IR are the respective AC and DC components ofthe infrared LED. Oxygenation derived from Ratrat using equation (5) issufficiently accurate for many applications when the condition (AC<<DC)is satisfied. Particularly, the approximation error is small when bothAC terms in equation (5) are less than ten percent of the related DCterms (i.e., both red and infrared modulations are less than 10%).

As stated above, oxygen saturation is related to Ratrat. Therelationship between Ratrat and oxygen saturation is typically plottedas a curve (i.e., saturation versus Ratrat) and stored as a table in thememory within the oximeter. Subsequently, a calculated Ratrat is used toindex the table to retrieve an entry in the table for the oxygensaturation estimate corresponding to that Ratrat. The estimation ofoxygen saturation using Ratrat is further described in U.S. Pat. Nos.4,911,167, 5,645,059, and 5,853,364.

Generally, the Red terms are measured in the red part of the opticalspectrum using the red LED, and the IR terms are measured in theinfrared part of the optical spectrum using the infrared LED. The ACterms are generated by the blood pressure pulse and are somewhat relatedto “perfusion.” The DC terms are (inversely) related to the “opacity”(or darkness) of the patient being monitored and are somewhat related to“translucence.” Generally, the four terms in equation (5) areindependent of each other. However, empirical studies suggest that thetwo DC terms are somewhat correlated (i.e., not wildly divergent), andpatients who are “opaque” tend to be opaque in both the red and infraredparts of the spectrum.

It has been determined that the magnitudes of the DC and AC componentsinfluence the accuracy of the saturation estimates and these magnitudesdepend on the sensor design being used, the specifications of componentsused in the sensor, and how the sensor has been applied to the patient.The invention advantageously utilizes this knowledge to provide anoximeter system capable of providing indications of the accuracy andreliability of the saturation estimates. Additional features areprovided by the invention based on the analysis of the measured DC andAC components, as described below.

FIG. 4 shows a signal quality diagram that includes data of the measuredDC and AC components. The vertical axis of the signal quality diagramcorresponds to the modulation percentage (Mod %) which is calculated asshown in equation (3) for each of the red and infrared signals. Thehorizontal axis corresponds to the DC component and is in units ofvirtual nano Amperes (nAv) and is given by equation (4). As shown inFIG. 4, both vertical and horizontal axes are plotted on a logarithmicscale.

As noted above, the detected optical waveform includes an AC componentand a DC component. The DC component is plotted on the horizontal axisand the ratio of AC to DC is expressed as a percentage (e.g., Mod %) andplotted on the vertical axis. Since two different optical signals aremeasured (i.e., for the red and infrared wavelengths), two points aregenerated and plotted on the signal quality diagram to uniquely identifythe AC and DC components of both the red and infrared optical signals.In FIG. 4, the data points corresponding to the red wavelength areidentified by a square and the data points corresponding to the infraredwavelength are identified by a diamond.

FIG. 4 shows the relative positions of two data points associated withtwo patients on the signal quality diagram. For a (stable) patient andover a short duration (i.e., of few pulses), all four Ratratconstituents (Red AC, DC; and Infrared AC, DC) remain approximatelyconstant. The data points for patient A indicate a patient with lowlight levels (i.e., low DC component values) and low modulation (i.e.,low Mod %). These data points could correspond to data from, forexample, a chubby, dark-skinned neonate who has poor perfusion, or areflectance sensor applied to a poorly perfused site (i.e., on thefoot). Conversely, the data points for patient B indicate a verytranslucent patient with good perfusion that results in high lightlevels and high modulation.

The pair of data points for each patient, one data point for redwavelength and one for infrared wavelength, defines the patient'scurrent (Ratrat) conditions. Equivalently, the pair of data pointsdescribes the oximeter's “operating point,” when the oximeter ismonitoring that patient. For a particular patient, the pair of datapoints can be used to estimate the patient's saturation using equation(5) and a table for saturation versus Ratrat. For example, the Ratratfor patient A is approximately 0.12/0.25 or 0.48. For a typicaloximeter, this Ratrat corresponds to a saturation of approximately 100%.The Ratrat for patient B is approximately 6/7 or 0.86, which correspondsto a saturation of approximately 85%.

In an embodiment, for each particular combination of oximeter model andsensor model, data points are collected for numerous “patients.” Thesedata points can be collected under a controlled test environment wheretrue oxygen saturation is known, and an accuracy of the saturationestimated from the red and infrared signals can be determined. Based onthe collected data, the diagram can be partitioned into regionscorresponding to different levels of quality and accuracy in thesaturation estimate. The regions also indicate a quality of the detectedsignals. Each region is defined by a signal boundary.

The signal boundaries are dependent on many factors such as the monitortype, sensor type, specifications of components in the sensor (e.g.,wavelength, LED characteristics), and other factors. In an embodiment,sensor specific boundaries are stored in the sensor memory or otherlocations associated with the sensor.

FIG. 5 shows a sensor signal quality diagram having defined regionscorresponding to different confidence levels in the saturation estimate.A display region 510 defines a portion of the signal quality diagramassociated with saturation estimates that satisfy a predeterminedquality and accuracy level and merit posting (or displaying) on themonitor. Display region 510 includes the set of “patient conditions”resulting in sufficiently accurate saturation estimates for a particularapplication. Accordingly, when the data points fall within displayregion 510, the saturation estimate (which is derived from the datapoints) is posted. Conversely, when the data points fall outside displayregion 510 into a non-display region 512, the saturation estimatecorresponding to these data points is not posted on the oximeterdisplay. Non-display region 512 lies outside, and generally surrounds,display region 510.

The DC signal corresponding to the red LED is generally “weaker” thanthe detected signal from the infrared LED. Since this characteristic isknown a priori, the oximeter can be designed to account for thisdifference. In one implementation, the red LED is associated with afirst display region and the infrared LED is associated with a seconddisplay region. For example, referring to FIG. 5, the red display regionis defined by lines 520, 522, 526, and 528, and the infrared displayregion is defined by lines 520, 524, 526, and 530. Since the red signalsare generally weaker than the infrared signal, the boundary of the reddisplay region tends to be closer to the lower left corner of the signalquality diagram.

The display region may be dependent on numerous operating conditions.For example, ambient light typically adds to the detected opticalsignals (i.e., increases the DC components) and thus may alter thedisplay region. In this case, the display region could be adjusted toaccount for the perturbation of the signal caused by the (or distortionintroduced by) ambient light.

FIG. 6 shows a signal quality diagram having defined display andnon-display regions (similar to those of FIG. 5) and a transition zone614. Transition zone 614 includes regions of the diagram that liebetween the display and non-display regions. The transition zonerepresents regions associated with a different (e.g., intermediate)quality and accuracy level than those of the display and non-displayregions. A different set of criteria can be used when evaluating datapoints that fall within the transition zone, as described below.

The regions shown in FIGS. 5 and 6 are only representatives of aparticular oximeter/sensor combination and for a particular set ofoperating conditions. Each oximeter (or each oximeter model or type) istypically associated with its own set of display and non-displayregions, which may differ from those shown in FIGS. 5 and 6. Someoximeters may even have poorly defined non-display regions, where theboundaries vary depending on a set of factors. These factors include thesignal-to-noise ratio (SNR) of the oximeter, the amount of ambientlight, the wavelength of the sensor LEDs, and so on.

In an embodiment, the oximeter operates in accordance with the followingset of rules:

-   -   If both data points (i.e., for the red and infrared signals)        fall within their respective display regions, the oximeter posts        the result (e.g., the saturation estimate, and heart rate).    -   If either data point falls within its non-display region, the        oximeter does not post the result.    -   In all other cases, the oximeter may or may not post the result.        These cases include instances in which one of the signals falls        in the transition zone and neither signal falls in the        non-display region.

Thus, the saturation estimate is posted if the modulation percentage(Mod %) and the light level (DC components) for both the red andinfrared wavelengths fall within the bounded areas of their respectivedisplay regions. In an embodiment, if the red signal falls within thered non-display region or if the infrared signal falls within theinfrared non-display region, or both, then the oximeter does not postthe saturation estimate. It can be noted that other sets of rules canalso be applied. For example, in another embodiment, the result isposted if one of the data points falls within its display region and theother data point falls within the transition zone. In yet anotherembodiment, the oximeter posts the saturation estimate and alsoindicates either the regions in which the data points fall or aconfidence level based on the regions in which the data points fall.

For clarity, FIG. 5 shows only display and non-display regions. Theseregions correspond to data points that are to be displayed and notdisplayed. However, additional regions can be defined within the signalquality diagram, with the additional regions corresponding to differentconfidence levels in the saturation estimate. Generally, the confidencelevel is high for data points that fall near the center of the diagramand decreases as the data points move away from the center. For theembodiment having multiple confidence levels, the oximeter can displaythe saturation estimate along with the confidence level.

For example, an “inactive” region can be defined and used to indicatewhen a sensor is not applied to a patient. The inactive region may beused to detect and notify when the sensor has been removed (i.e., fallenoff) the patient. The inactive region lies outside the display andtransition regions, correlates to measurements from sensors that are notattached to patients, and typically comprises a portion of thenon-display region. This region can be defined through simulation orthrough empirical measurements. The oximeter computes the data points inthe manner described above. If the data points fall inside the inactiveregion, the oximeter displays an indication that the sensor has beenremoved from the patient.

FIG. 7 shows a flow diagram of an embodiment of the measurement displayprocess of the invention. At a step 712, one or more signals indicativeof a physiological parameter are detected. For an oximeter used tomeasure oxygen saturation, this detecting step may include, for example,receiving optical signals from two LEDs and conditioning these signals.At a step 714, the detected signal(s) are processed to generateintermediate data points. For oxygen saturation, this processing stepmay include filtering the data samples to generate DC and AC components,and using these components to generate the modulation percentage (Mod%). The intermediate data points would include filtered values for theDC component and computed values of the modulation percentage. Theintermediate data points are then compared against a signal qualitydiagram (step 716). This diagram is generated previously, in a mannerdescribed above.

At step 718, it is determined whether the intermediate data points fallwithin the display region. If the answer is yes, the physiologicalparameter is estimated based on the detected and processed signal(s).For example, the oxygen saturation can be estimated from the computedMod % for the two LEDs using equation (5). At step 722, the estimatedphysiological parameter is displayed, and the process terminates.

If it is determined at step 718 that the data points do not fall withinthe display region, a determination is made whether the data points fallwithin the inactive region (step 724). If the answer is yes, an errormessage is displayed at step 726. This error message may inform theclinician of the error data points (e.g., “ERROR MEASUREMENT”), providea suggestion (e.g., “TRY ANOTHER SITE”), and so on. The process thenterminates. In some embodiments of the invention, step 724 is notperformed.

If it is determined at step 724 that the data points do not fall withinthe inactive region, a determination is made whether the data pointsfall within the non-display region, at a step 730. If the answer is yes,the measurement is not displayed. An error message may be displayed toinform the clinician. This error message may inform the clinician of theinvalid data points (e.g., “INVALID MEASUREMENT” or “WEAK SIGNAL”),provide a suggestion (e.g., “TRY ANOTHER SITE”), and so on. The processthen terminates.

If it is determined at step 730 that the data points do not fall withinthe non-display region, a determination is made whether the data pointsfall within the transition region, at step 736. If the answer is yes, awarning message may be displayed to warn the clinician. This warningmessage may indicate that the data points are of questionable accuracy(e.g., “INACCURATE MEASUREMENT” or “WEAK SIGNAL”), provide a suggestion(e.g., “TRY ANOTHER SITE”), and so on. The physiological parameter mayalso be computed and displayed along with the warning message. Theprocess then terminates. In some embodiments of the invention, step 736is not performed.

FIG. 8 shows a signal quality diagram with data collected from a patientpopulation. The patient data can be used to define the display andnon-display regions, to characterize the patient population's meanmodulation percentage and mean nAv for both red and infraredwavelengths, to characterize measurement ambiguity that is indicative ofthe instrument's accuracy, or a combination of the above. Ambiguity asused herein, which is an approximate indication of instrument error, isthe sum of the mean error (bias) of an instrument and the stability ofthe readings obtained (wander). The stability of the readings obtained(wander) is the standard deviation of the instrument readings.

The ambiguity, or estimated error, for various combinations ofmodulation and DC component are then plotted on the signal qualitydiagram. The average saturation, saturation bias, saturation wander, andambiguity can be computed using equal weighting (i.e., giving the sameimportance for each data point) or unequal weighting that accounts forpopulation statistics (i.e., giving less importance to data points thatoccur more rarely). Signal specification boundaries can also be obtainedfor a particular patient sub-population (e.g., perinatal patients) tofurther improve accuracy in the measurement reporting when theinstrument is used for that particular patient sub-population.

FIG. 9 shows a signal quality diagram that includes ambiguity contoursplotted over a portion of the display region. Each contour linecorresponds to a particular ambiguity, in saturation points. As anexample, at an infrared operating point of 10 nAv and three percentmodulation, the plots show an ambiguity of between 10 and 12 saturationpoints. The contour lines can be generated by collecting data points,grouping the data points that have similar infrared DC components, andselecting a representative ambiguity for those data points. The selectedambiguities for the groups of data points are plotted as atwo-dimensional contour plot.

In an embodiment, the largest ambiguity in each group is selected asrepresentative of the group and a contour plot of the worse caseambiguity is generated. This information is useful, for example, in anoximeter having a guaranteed limit on the saturation ambiguity, and onlydata points within the guaranteed limit are posted. Other variations ofthe contour plots shown in FIG. 9 are possible. For example, contourplots can be generated for: (1) the worst case ambiguity, (2) theaverage ambiguity, (3) the worst case or average absolute value of thebias, (4) the worst case or average value of the wander, and others. Theaverage ambiguity contour plots are generated based on the average ofthe ambiguities obtained for each group, and are useful for indicatingtypical ambiguity that is likely to occur for that modulation andinfrared DC component.

The contour plots on the signal quality diagram can also be adjustedfor, or take into account, different pulse rates and abnormal heartrhythms such as arrhythmias, premature ventricular contractions,bigeminy, fibrillation, cardiac arrest, and other cardiac pathologies.

The invention provides advantages not available in conventionaloximeters. For example, by detecting data points corresponding tosaturation estimates having a low degree of confidence and discardingthese estimates (or indicating the low degree of confidence), theinvention provides an oximeter having improved diagnostic accuracy andreliability. This ensures that the results relied upon by the clinicianmeet a predetermined reliability criteria. The invention may also beused to detect and notify when the sensor has been removed (i.e., fallenoff) the patient, as described above.

The oximeter of the invention can also be used to assist the cliniciantake more accurate measurements. This is a particularly usefulapplication of the invention since it is known that some clinicians movethe sensor to various parts of the patient in an attempt to obtainbetter readings. To assist the clinician, the oximeter can be programmedto display an indicator signal that indicates whether a selected site isgood or poor for application of the sensor. This prompt may also be usedto assist a less experienced clinician administer the saturationmeasurement.

The invention can be used for various physiological measurements. Theapplication of the invention to pulse oximetry has been described asonly one preferred embodiment. The invention can also be applied toother physiological measurements such as ECG, blood pressure,temperature, heart rate, and so on. Accordingly, the invention is not tobe limited for use only with oximetry or pulse oximetry.

The foregoing description of the preferred embodiments is provided toenable any person skilled in the art to make or use the presentinvention. Various modifications to these embodiments will be readilyapparent to those skilled in the art, and the generic principles definedherein may be applied to other embodiments without the use of furtherinvention. For example, the invention can be applied to measurements ofother physiological characteristics. Thus, the present invention is notintended to be limited to the embodiments shown herein but is to beaccorded the widest scope consistent with the principles and novelfeatures disclosed herein.

1-22. (canceled)
 23. A method of manufacturing a system, comprising:providing a sensor comprising a detector configured to generate signalsthat are indicative of a physiological characteristic of a patient;providing a memory coupled to the sensor, the memory storing datadefining at least one sensor signal specification boundary for thesignals, the at least one sensor signal specification boundary beingindicative of a quality of the signals and an accuracy of an estimatedphysiological condition of the patient; and providing a monitorconfigured to receive the signals indicative of the physiologicalcharacteristic from the sensor, to provide the estimated physiologicalcondition of the patient based on the signals, to receive the datadefining the at least one sensor signal specification boundary for thesignals from the sensor, to compare the signals against the at least onesensor signal specification boundary, and to generate an indication ofthe accuracy of the estimated physiological condition.
 24. The method ofclaim 23, wherein the sensor signal specification boundary includes oneor both of limits for an AC modulation component and limits for a DCcomponent.
 25. The method of claim 24, wherein the monitor is configuredto calculate values having AC and DC components from the signals. 26.The method of claim 25, wherein the AC and DC components are dependenton either a physiological status of the patient, sensor type, or sensorlocation.
 27. The method of claim 22, wherein the physiologicalcharacteristic comprises arterial oxygen saturation.
 28. A method ofoperating a system for detecting at least one physiologicalcharacteristic of a patient, comprising: generating, with a sensor,signals from the patient that are indicative of the physiologicalcharacteristic; accessing a memory coupled to the sensor to facilitatetransmission of data defining at least one sensor signal specificationboundary, the at least one sensor signal specification boundary beingindicative of a quality of the signals and an accuracy of an estimatedphysiological condition of the patient; transmitting from the sensor toa monitor the signals indicative of the at least one physiologicalcharacteristic; determining the estimated physiological condition of thepatient via the monitor based on the signals; transmitting data definingthe at least one sensor signal specification boundary for the signalsfrom the sensor to the monitor; comparing via the monitor the signalsagainst the sensor signal specification boundary; and generating via themonitor an indication of the accuracy of the estimated physiologicalcondition.
 29. The method of claim 28, wherein the sensor signalspecification boundary includes one or both of limits for an ACmodulation component and limits for a DC component.
 30. The method ofclaim 29, comprising calculating via the monitor values having AC and DCcomponents from the signals.
 31. The method of claim 30, wherein the ACand DC components are dependent on either a physiological status of thepatient, sensor type, or sensor location.
 32. The method of claim 28,wherein the physiological characteristic comprises arterial oxygensaturation.
 33. A monitor for providing an indication of an accuracy ofan estimated physiological condition of a patient, the monitor beingcoupleable to a sensor that generates signals indicative of at least onephysiological characteristic of the patient, the monitor comprising: afirst receiving circuit configured to receive the signals from thesensor; a first processing circuit configured to provide an estimatedphysiological condition of the patient based on the signals; a secondreceiving circuit configured to receive data defining at least onesensor signal specification boundary for the signals from the sensor,the sensor signal specification boundary being indicative of a qualityof the signals and an accuracy of the estimated physiologicalcharacteristic; and a second processing circuit configured to comparethe signals against the at least one sensor signal specificationboundary and to generate an indication of the accuracy of the estimatedphysiological condition.
 34. The monitor of claim 33, wherein the sensorsignal specification boundary includes one or both of limits for an ACmodulation component and limits for a DC component.
 35. The monitor ofclaim 34, comprising a third processing circuit configured to calculatevalues having AC and DC components from the signals.
 36. The monitor ofclaim 35, wherein the AC and DC components are dependent on either aphysiological status of the patient, sensor type, or sensor location.37. The monitor of claim 33, wherein the physiological characteristiccomprises arterial oxygen saturation.
 38. A system for detecting atleast one physiological characteristic of a patient, comprising: asensor, comprising: a detector configured to generate signals that areindicative of the at least one physiological characteristic; a memorycoupled to the sensor, the memory storing data defining at least onesensor signal specification boundary for the signals, the sensor signalspecification boundary being indicative of a quality of the signals andan accuracy of an estimated physiological condition of the patient,wherein the sensor signal specification boundary includes limits for anAC modulation component and DC component of the signals; and anintegrated circuit providing access to the memory to facilitatetransmission of the data defining the at least one sensor signalspecification boundary; and a monitor, comprising: a receiving circuitconfigured to receive communications relating to signals indicative ofthe at least one physiological characteristic from the sensor and datadefining the at least one sensor signal specification boundary for thegenerated signals from the sensor; and a processing circuit configuredto determine the estimated physiological condition of the patient basedon the signals, compare the signals against the at least one sensorsignal specification boundary, generate an indication of the accuracy ofthe estimated physiological condition, and determine whether thereceived signals are within a normal signal regime or an abnormal signalregime.
 39. The system of claim 38, wherein the processing circuit isconfigured to calculate values having AC and DC components from thesignals.
 40. The system of claim 39, wherein the AC and DC componentsare dependent on either a physiological status of the patient, sensortype, or sensor location.
 41. The system of claim 38, wherein themonitor comprises an alarm that is triggered when the signals move fromthe normal regime to the abnormal regime.
 42. The system of claim 38,wherein the physiological characteristic comprises arterial oxygensaturation.